Cover Image

A Systematic Literature Review of Spatio-Temporal Graph Neural Network Models for Time Series Forecasting and Classification

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Corradini, Flavio, Gerosa, Flavio, Gori, Marco, Lucheroni, Carlo, Piangerelli, Marco, Zannotti, Martina
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence Data Analysis, Statistics and Probability
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Complex-Valued Time Series Based Solar Irradiance Forecast
by: Voyant, Cyril, et al.
Published: (2022)

Temporal Graph Neural Networks for Early Anomaly Detection and Performance Prediction via PV System Monitoring Data
by: Mukherjee, Srijani, et al.
Published: (2025)

Benchmarks for Solar Radiation Time Series Forecasting
by: Voyant, Cyril, et al.
Published: (2022)

Complexity of Financial Time Series: Multifractal and Multiscale Entropy Analyses
by: Masoudi, Oday, et al.
Published: (2025)

Tunnelling Through Time Series: A Probabilistic Visibility Graph for Local and Global Pattern Discovery
by: Sotero, Roberto, et al.
Published: (2025)

Out-of-Sample Hydrocarbon Production Forecasting: Time Series Machine Learning using Productivity Index-Driven Features and Inductive Conformal Prediction
by: Idris, Mohamed Hassan Abdalla, et al.
Published: (2025)

Predictability Analysis and Prediction of Discrete Weather and Financial Time-Series Data with a Hamiltonian-Based Filter-Projection Approach
by: Kiefer, Henrik, et al.
Published: (2024)

Renormalized Graph Representations for Node Classification
by: Caso, Francesco, et al.
Published: (2023)

Evidential Reconstruction of Network from Time Series
by: Xian, Yishu, et al.
Published: (2026)

Classification of Hoyle State Decay Branches in Active Target Time Projection Chamber using Neural Network
by: Das, Pralay Kumar, et al.
Published: (2025)

Symmetry-Constrained Forecasting of Periodically Correlated Energy Processes
by: Voyant, Cyril, et al.
Published: (2026)

Robust Causal Discovery in Real-World Time Series with Power-Laws
by: Tusoni, Matteo, et al.
Published: (2025)

Enhanced Spatial Clustering of Single-Molecule Localizations with Graph Neural Networks
by: Pineda, Jesús, et al.
Published: (2024)

Application of the Allan Variance to Time Series Analysis in Astrometry and Geodesy: A Review
by: Malkin, Zinovy
Published: (2016)

Accurate Memory Kernel Extraction from Discretized Time Series Data
by: Tepper, Lucas, et al.
Published: (2024)

Cryptocurrency Time Series on the Binary Complexity-Entropy Plane: Ranking Efficiency from the Perspective of Complex Systems
by: Pinto, Erveton P., et al.
Published: (2025)

Temporal scaling theory for bursty time series with clusters of arbitrarily many events
by: Jo, Hang-Hyun, et al.
Published: (2024)

Novel computational approaches for ratio distributions with an application to Hake's ratio in effect size measurement
by: Hanč, Jozef, et al.
Published: (2024)

Astrometric Binary Classification Via Artificial Neural Networks
by: Smith, Joe
Published: (2024)

Emerging Activity Temporal Hypergraph: a model for generating realistic time-varying hypergraphs
by: Mancastroppa, Marco, et al.
Published: (2025)

Spatio-temporal analysis of sprays by using Phase Doppler Anemometry data
by: Rácza, Erika, et al.
Published: (2025)

Learnability Window in Gated Recurrent Neural Networks
by: Livi, Lorenzo
Published: (2025)

Beyond Classical Models: Statistical Physics Tools for the Analysis of Time Series in Modern Air Transport
by: Olivares, Felipe, et al.
Published: (2025)

Replacing Gaussian Processes with Neural Networks in Pulsar Timing Array Inference of the Gravitational-Wave Background
by: Tiruvaskar, Shreyas, et al.
Published: (2026)

Time Series of Magnetic Field Parameters of Merged MDI and HMI Space-Weather Active Region Patches as Potential Tool for Solar Flare Forecasting
by: Kosovich, Paul A., et al.
Published: (2024)

Towards a Unified Formalism of Multivariate Coefficients of Variation -- Application to the Analysis of Polarimetric Speckle Time Series
by: Colin, Elise, et al.
Published: (2024)

Enhancing Graph Topology and Clustering Quality: A Modularity-Guided Approach
by: Wang, Yongyu, et al.
Published: (2023)

Turning Time Series into Algebraic Equations: Symbolic Machine Learning for Interpretable Modeling of Chaotic Time Series
by: Panja, Madhurima, et al.
Published: (2026)

Convolutional Neural Networks For Turbulent Model Uncertainty Quantification
by: Chu, Minghan, et al.
Published: (2024)

Graph Frequency Features of Cancer Gene Co-Expression Networks
by: Adel, Radwa, et al.
Published: (2023)

Robust Lifetime Estimation from HPGe Radiation-Sensor Time Series Using Pairwise Ratios and MFV Statistics
by: Golovko, Victor V.
Published: (2025)

Toward Dynamic Stability Assessment of Power Grid Topologies using Graph Neural Networks
by: Nauck, Christian, et al.
Published: (2022)

Exploring the Statistical Properties of Outputs from a Process Inspired by Geometrical Interpretation of Newton's Method
by: Kirouani, Taki
Published: (2024)

Estimating Nodal Spreading Influence Using Partial Temporal Network
by: Mao, Tianrui, et al.
Published: (2025)

A General Solution for Network Models with Pairwise Edge Coupling
by: Catanzaro, Alessio, et al.
Published: (2025)

Active Learning with Fully Bayesian Neural Networks for Discontinuous and Nonstationary Data
by: Ziatdinov, Maxim
Published: (2024)

Efficient Training of Deep Neural Operator Networks via Randomized Sampling
by: Karumuri, Sharmila, et al.
Published: (2024)

Memory Effects, Multiple Time Scales and Local Stability in Langevin Models of the S&P500 Market Correlation
by: Wand, Tobias, et al.
Published: (2023)

End-to-End Multi-Track Reconstruction using Graph Neural Networks at Belle II
by: Reuter, Lea, et al.
Published: (2024)

Effectiveness of Contact Tracing on Networks with Cliques
by: Rizi, Abbas K., et al.
Published: (2023)